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An Augmented Reality Based Human-Robot Interaction Interface Using Kalman Filter Sensor Fusion.

Chunxu Li1,2, Ashraf Fahmy3,4, Johann Sienz5

  • 1ASTUTE 2020 (Advanced Sustainable Manufacturing Technologies), Swansea University, Swansea SA1 8EN, UK. chunxu.li@swansea.ac.uk.

Sensors (Basel, Switzerland)
|October 27, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an Augmented Reality (AR) system for intuitive robot control, using LeapMotion and Kinect sensors for precise hand tracking and motion sensing. The developed AR interface enhances remote robot teleoperation accuracy and ease of use.

Keywords:
Kalman filter sensor fusionKinect sensorLeapMotion sensoraugmented realityhuman-robot interaction

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Augmented Reality

Background:

  • Remote robot control often faces challenges with precision and ease of interaction.
  • Existing methods may lack immersive feedback and intuitive control mechanisms.

Purpose of the Study:

  • To develop an Augmented Reality (AR) system for enhanced remote robot control and adjustment.
  • To improve the accuracy and ease of human-robot interaction in teleoperation tasks.

Main Methods:

  • Utilized LeapMotion sensor for hand gesture and position tracking.
  • Employed Kinect V2 camera for measuring 3D motion velocities.
  • Developed an Unreal Engine 4 based AR environment for immersive monitoring.
  • Implemented Kalman filtering (KF) for sensor data fusion (position and velocity).
  • Used User Datagram Protocol (UDP) for real-time data transmission to a Baxter robot.

Main Results:

  • Successfully tracked operator hand movements and gestures.
  • Achieved accurate measurement of motion velocities in x, y, z directions.
  • Demonstrated immersive robot control monitoring within the AR environment.
  • Validated the effectiveness of the KF algorithm in fusing sensor data for optimal control signals.
  • Enabled real-time teleoperation of a Baxter robot.

Conclusions:

  • The proposed AR system significantly enhances the intuitiveness and precision of remote robot control.
  • Sensor fusion via Kalman filtering provides robust and accurate data for teleoperation.
  • The developed system offers a promising approach for advanced human-robot collaboration in remote settings.